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In this work, by employing a bitsliced data representation as building blocks of algorithms, we showcase the capability and scalability of our proposed method in a variety of PRNG methods in the category of block and stream ciphers. While…

Cryptography and Security · Computer Science 2019-10-22 Saleh Khalaj Monfared , Omid Hajihassani , Soroush Meghdadi Zanjani , Mohammadsina Kiarostami , Dara Rahmati , Saeid Gorgin

We provide an overview of the status of Monte-Carlo event generators for high-energy particle physics. Guided by the experimental needs and requirements, we highlight areas of active development, and opportunities for future improvements.…

High Energy Physics - Phenomenology · Physics 2025-02-28 J. M. Campbell , M. Diefenthaler , T. J. Hobbs , S. Höche , J. Isaacson , F. Kling , S. Mrenna , J. Reuter , S. Alioli , J. R. Andersen , C. Andreopoulos , A. M. Ankowski , E. C. Aschenauer , A. Ashkenazi , M. D. Baker , J. L. Barrow , M. van Beekveld , G. Bewick , S. Bhattacharya , N. Bhuiyan , C. Bierlich , E. Bothmann , P. Bredt , A. Broggio , A. Buckley , A. Butter , J. M. Butterworth , E. P. Byrne , C. M. Carloni Calame , S. Chakraborty , X. Chen , M. Chiesa , J. T. Childers , J. Cruz-Martinez , J. Currie , N. Darvishi , M. Dasgupta , A. Denner , F. A. Dreyer , S. Dytman , B. K. El-Menoufi , T. Engel , S. Ferrario Ravasio , D. Figueroa , L. Flower , J. R. Forshaw , R. Frederix , A. Friedland , S. Frixione , H. Gallagher , K. Gallmeister , S. Gardiner , R. Gauld , J. Gaunt , A. Gavardi , T. Gehrmann , A. Gehrmann-De Ridder , L. Gellersen , W. Giele , S. Gieseke , F. Giuli , E. W. N. Glover , M. Grazzini , A. Grohsjean , C. Gütschow , K. Hamilton , T. Han , R. Hatcher , G. Heinrich , I. Helenius , O. Hen , V. Hirschi , M. Höfer , J. Holguin , A. Huss , P. Ilten , S. Jadach , A. Jentsch , S. P. Jones , W. Ju , S. Kallweit , A. Karlberg , T. Katori , M. Kerner , W. Kilian , M. M. Kirchgaeßer , S. Klein , M. Knobbe , C. Krause , F. Krauss , J. Lang , J. -N. Lang , G. Lee , S. W. Li , M. A. Lim , J. M. Lindert , D. Lombardi , L. Lönnblad , M. Löschner , N. Lurkin , Y. Ma , P. Machado , V. Magerya , A. Maier , I. Majer , F. Maltoni , M. Marcoli , G. Marinelli , M. R. Masouminia , P. Mastrolia , O. Mattelaer , J. Mazzitelli , J. McFayden , R. Medves , P. Meinzinger , J. Mo , P. F. Monni , G. Montagna , T. Morgan , U. Mosel , B. Nachman , P. Nadolsky , R. Nagar , Z. Nagy , D. Napoletano , P. Nason , T. Neumann , L. J. Nevay , O. Nicrosini , J. Niehues , K. Niewczas , T. Ohl , G. Ossola , V. Pandey , A. Papadopoulou , A. Papaefstathiou , G. Paz , M. Pellen , G. Pelliccioli , T. Peraro , F. Piccinini , L. Pickering , J. Pires , W. Płaczek , S. Plätzer , T. Plehn , S. Pozzorini , S. Prestel , C. T. Preuss , A. C. Price , S. Quackenbush , E. Re , D. Reichelt , L. Reina , C. Reuschle , P. Richardson , M. Rocco , N. Rocco , M. Roda , A. Rodriguez Garcia , S. Roiser , J. Rojo , L. Rottoli , G. P. Salam , M. Schönherr , S. Schuchmann , S. Schumann , R. Schürmann , L. Scyboz , M. H. Seymour , F. Siegert , A. Signer , G. Singh Chahal , A. Siódmok , T. Sjöstrand , P. Skands , J. M. Smillie , J. T. Sobczyk , D. Soldin , D. E. Soper , A. Soto-Ontoso , G. Soyez , G. Stagnitto , J. Tena-Vidal , O. Tomalak , F. Tramontano , S. Trojanowski , Z. Tu , S. Uccirati , T. Ullrich , Y. Ulrich , M. Utheim , A. Valassi , A. Verbytskyi , R. Verheyen , M. Wagman , D. Walker , B. R. Webber , L. Weinstein , O. White , J. Whitehead , M. Wiesemann , C. Wilkinson , C. Williams , R. Winterhalder , C. Wret , K. Xie , T-Z. Yang , E. Yazgan , G. Zanderighi , S. Zanoli , K. Zapp

In this work, we argue that the implications of Pseudo and Quantum Random Number Generators (PRNG and QRNG) inexplicably affect the performances and behaviours of various machine learning models that require a random input. These…

Machine Learning · Computer Science 2019-10-11 Jordan J. Bird , Anikó Ekárt , Diego R. Faria

In this paper, we propose ThundeRiNG, a resource-efficient and high-throughput system for generating multiple independent sequences of random numbers (MISRN) on FPGAs. Generating MISRN can be a time-consuming step in many applications such…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-05-21 Hongshi Tan , Xinyu Chen , Yao Chen , Bingsheng He , Weng-Fai Wong

Monte Carlo event generators are an essential tool for data analysis in collider physics. To include subleading quantum corrections, these generators often need to produce negative weight events, which leads to statistical dilution of the…

High Energy Physics - Phenomenology · Physics 2020-10-21 Benjamin Nachman , Jesse Thaler

A machine learning technique is used to fit multiplicity distributions in high-energy proton-proton collisions and applied to make predictions for collisions at higher energies. The method is tested with Monte Carlo event generator events.…

High Energy Physics - Experiment · Physics 2021-08-16 E. Shokr , A. De Roeck , M. A. Mahmoud

We review the physics basis, main features and use of general-purpose Monte Carlo event generators for the simulation of proton-proton collisions at the Large Hadron Collider. Topics included are: the generation of hard-scattering matrix…

$\mathbf F_2$-linear pseudorandom number generators are very popular due to their high speed, to the ease with which generators with a sizable state space can be created, and to their provable theoretical properties. However, they suffer…

Data Structures and Algorithms · Computer Science 2022-03-29 David Blackman , Sebastiano Vigna

Machine learning potentials (MLPs) are widely applied as an efficient alternative way to represent potential energy surfaces (PES) in many chemical simulations. The MLPs are often evaluated with the root-mean-square errors on the test set…

We present results of extensive bit level tests on some pseudorandom number generators which are commonly used in physics applications. The generators have first been tested with an extended version of the $d$-tuple test. Second, we have…

High Energy Physics - Lattice · Physics 2009-10-22 K. Kankaala , T. Ala-Nissila , I. Vattulainen

Monte Carlo particle transport problems play a vital role in scientific computing, but solving them on exiting von Neumann architectures suffers from random branching and irregular memory access, causing computing inefficiency due to a…

Hardware Architecture · Computer Science 2026-03-31 Siqing Fu , Lizhou Wu , Tiejun Li , Xuchao Xie , Chunyuan Zhang , Sheng Ma , Jianmin Zhang , Yuhan Tang , Jixuan Tang

Machine learning tools are commonly used in modern high energy physics (HEP) experiments. Different models, such as boosted decision trees (BDT) and artificial neural networks (ANN), are widely used in analyses and even in the software…

Data Analysis, Statistics and Probability · Physics 2016-12-21 A. Rogozhnikov

Monte Carlo simulations are based on the manipulation of random numbers to evaluate probable outcomes, with applicability in a variety of different fields. By assigning probabilities, which can be determined a priori, to various events, it…

Physics Education · Physics 2022-01-03 Parasuraman Swaminathan

Empirical tests for pseudorandom number generators based on the use of processes or physical models have been successfuly used and are considered as complementary to theoretical test of randomness. In this work a statistical methodology for…

Computational Physics · Physics 2011-11-09 H. F. Coronel-Brizio , A. R. Hernandez-Montoya , M. A. Jimenez-Montano , L. E. Mora-Forsbach , .

Numerical simulations of models and theories that describe complex systems such as spin glasses are becoming increasingly important. Beyond fundamental research, these computational methods also find practical applications in fields like…

Equipping the probability space with a local Dirichlet form with square field operator \Gamma and generator A allows to improve Monte Carlo simulations of expectations and densities as soon as we are able to simulate a random variable X…

Probability · Mathematics 2013-01-29 Nicolas Bouleau

The status of two Monte Carlo generators, HELAC-PHEGAS, a program for multi-jet processes and VBFNLO, a parton level program for vector boson fusion processes at NLO QCD, is briefly presented. The aim of these tools is the simulation of…

High Energy Physics - Phenomenology · Physics 2008-11-26 Malgorzata Worek

We study the relationship between notions of pseudorandomness in the quantum and classical worlds. Pseudorandom quantum state generator (PRSG), a pseudorandomness notion in the quantum world, is an efficient circuit that produces states…

Quantum Physics · Physics 2023-09-15 Prabhanjan Ananth , Yao-Ting Lin , Henry Yuen

Particle transport in random media obeying a given mixing statistics is key in several applications in nuclear reactor physics and more generally in diffusion phenomena emerging in optics and life sciences. Exact solutions for the…

Statistical Mechanics · Physics 2017-06-07 Colline Larmier , Andrea Zoia , Fausto Malvagi , Eric Dumonteil , Alain Mazzolo

We address the problem of detecting deviations of binary sequence from randomness,which is very important for random number (RNG) and pseudorandom number generators (PRNG). Namely, we consider a null hypothesis $H_0$ that a given bit…

Information Theory · Computer Science 2007-07-13 B. Ya. Ryabko , V. A. Monarev